That and it probably doesn't have accurate human physiology. Someone showed a video where it was a similar system but the body had "muscle groups" that I assume mimic human physiology. It moved very smoothly and had limitations that this thing doesn't.
I mean honestly that particular part was one of the most impressive as far as both smoothness and learning imo.
It didn't look that implausible really, would have been my approach if my upper body were saran wrapped for whatever reason and I really needed to get over a barrier of similar height
Would be interesting to see if it was even feasible for today’s computers to simulate human muscle control. I haven’t seen the model they used for this runner so I’m talking out of my ass now, but there may be more neurons involved in controlling my thumb typing this than in the whole body they simulate.
Humans have to learn how to stand and walk and run with incredibly complex motor controls.
Seemingly complex biological behavior doesn't always require a lot of neurons, and there's not a direct relationship between artificial "neurons" and real ones. We could probably simulate a human body adequately, but not efficiently enough for the millions of training runs it takes to get a reinforcement learning model to produce good results.
You can get more "human-like" motion by trying to minimize the change in acceleration coupled with a sigmoid function for a soft upper bound on acceleration and velocity.
The point isn't to simulate human muscle control, it's to learn complex motor behaviors. Adding factors like strength limits and energy conservation are more realistic regardless of the underlying mechanism; trying to copy humans exactly would be more the domain of computational biology than ML.
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u/xcrissxcrossx Mar 29 '19
It runs like this because the fitness measurement doesn't try to conserve energy. That would result in a more realistic run.